We present multiple-image encryption (MIE) based on compressive holography. In the encryption, a holographic technique is employed to record multiple images simultaneously to form a hologram. The twodimensional Fourier data of the hologram are then compressed by nonuniform sampling, which gives rise to compressive encryption. Decryption of individual images is cast into a minimization problem. The minimization retains the sparsity of recovered images in the wavelet basis. Meanwhile, total variation regularization is used to preserve edges in the reconstruction. Experiments have been conducted using holograms acquired by optical scanning holography as an example. Computer simulations of multiple images are subsequently demonstrated to illustrate the feasibility of the MIE scheme.

Abstract. Multiple image encryption (MIE) was proposed to increase the efficiency of encrypting images by processing several images simultaneously. Because of the advantage of optical technology in processing twodimensional images at high throughput, MIE has been significantly improved by use of methods originating from optics. Phase retrieval was the process of algorithmically finding solutions to the phase loss problem due to light detectors only capturing the intensity. It was to retrieve phase information for the determination of a structure from diffraction data. Error-reduction algorithm is a typical phase retrieval method. Here, we employ it to illustrate that methods in phase retrieval are able to encrypt multiple images and compress them into encrypted data simultaneously. Moreover, the decryption is also designed to handle multiple images at the same time. The whole process including both the encryption and decryption is proposed to improve MIE with respect to the compression and efficiency. The feasibility and encryption of the MIE scheme is demonstrated with encryption experiments under Gaussian white noise and unauthorized access.

Normal fNIRS setting up was limited by superficial physiological noises when applied into the deception detection. We designed a hybrid-pair wireless fNIRS system to improve the detection. The system takes advantages of short-pair channel to suppress the effect of physiological noises, and wireless module to improve the comfortableness of wearing it. We applied the system into a modified Guilty Knowledge Test. The experiment demonstrated that normal metrics might hint different energy consume during lying, while the regional oxygen saturation rSO2, specific in the system, is sensitive to indicate a lying.

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This paper presents a scheme of a multiple-image compressed encryption based on the compressive holography technique. Computer generate hologram (CGH) is implemented to record multiple images simultaneously into an encrypted hologram. Because its two-dimensional (2D) Fourier transform (FT) result is analogous a partial 3D Fourier transform sampling, the 2D FT result can be compressed by a nonuniform sampling accompanied with a quantization. The encryption and compression processes agrees with the requirement of the compressive sensing and composes the compressive holography. Therefore, the decryption is solved by a minimization. It remains the sparsity of the recovered natural images in the wavelet basis. Meanwhile, a total-variation regularization and a nonnegative constraint is employed to extract images with edge preserved and nonnegative gray scale, respectively. Experiments are conducted to demonstrate the feasibility of the multipleimage compressed encryption.